Application of adaptive chirp mode decomposition on parameter identification of sub/super‐synchronous oscillation signals

Abstract

Identifying the parameters of sub/super‐synchronous oscillation (SubSO/SupSO) signals is challenging, because (1) the mode numbers of the oscillation signals are unknown, and (2) the oscillation signals are non‐stationary and noisy. The non‐stationary components need to be accurately identified in order to efficiently suppress SubSO/SupSO. Here, an adaptive chirp mode decomposition (ACMD) method joining a synchroextracting transform (SET) is exploited. First, for detecting the initial instantaneous frequencies (IFs) of SubSO and SupSO, SET is employed to provide time–frequency representations with satisfied energy concentration to ACMD. Second, ACMD is applied to decomposing the main components from the oscillation signal without needing to use the mode numbers, and directly compute the final IFs and instantaneous amplitudes (IAs) for SubSO and SupSO without Hilbert transform. And third, the damping factors of the SubSO and SupSO are further identified with the IAs. The proposed method is evaluated over synthetic signals, simulation data, and real field data from a wind system. Experimental results demonstrate that, compared with the classical signal decomposition‐based identification methods, the proposed method more accurately detects frequencies, amplitudes, and damping factors of SubSO and SupSO components for non‐stationary and noisy signals.

A black‐box method for the stability analysis of multi‐inverter‐fed power systems using Bode diagrams

“…Stability analysis approaches for a multi-inverter-fed power system should adapt to the replacement of synchronous generators in traditional power systems by clean, inverter-based resources [1]. Unstable problems, such as those induced by the coupling between grids and grid-connected inverters (GCIs), have been analysed [2][3][4]. The internal parameters, control methods, structure, and other information pertaining to gridconnected inverters at engineering sites are unknown owing to the technical confidentiality restrictions imposed by the equipment supplier.…”

Two-step PV grid-connected inverter control parameter identification based on improved gray wolf algorithm

“…[5] But the least square method belongs to the linear estimation, the default system is linear relationship, use has certain limitations. [6] In reference [7] , a parameter identification method of photovoltaic array based on the hybrid algorithm of artificial fish swarm and leapfrog was proposed. Referrnce [8] proposes a parameter identification strategy based on gray wolf algorithm.…”

A Grey Box Method for the Stability Analysis of Multi-Inverter-Fed Power Systems using Bode Diagrams

“…Stability analysis approaches for a multi-inverterfed power system should adapt to the replacement of synchronous generators in traditional power systems by clean, inverter-based resources [1]. Unstable accidents, such as those induced by the coupling between grids and grid-connected inverters (GCIs), have been reported [2][3][4]. The internal parameters, control methods, structure, and other information pertaining to grid-connected inverters at engineering sites are unknown owing to the technical confidentiality restrictions imposed by the equipment supplier.…”